Evaluation of waste recycling of fruits based on Support Vector Machine (SVM)
The purpose of this research is to investigate the effect of innovation management on recycling products and to use a new method based on artificial intelligence and a machine learning for innovative product recycled management. To this end, 170 employees of fruit and berry fields were selected amon...
Gespeichert in:
| Veröffentlicht in: | Cogent environmental science 2020, Vol.6 (1) |
|---|---|
| Hauptverfasser: | , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | 1 |
| container_start_page | |
| container_title | Cogent environmental science |
| container_volume | 6 |
| creator | Farjami, Javad Dehyouri, Sahar Mohamadi, Mohamad |
| description | The purpose of this research is to investigate the effect of innovation management on recycling products and to use a new method based on artificial intelligence and a machine learning for innovative product recycled management. To this end, 170 employees of fruit and berry fields were selected among the municipality of Tehran in 2015 by proportional sampling method. A researcher-made questionnaire was used to measure the attitude towards waste recycling and recycling behavior. To calculate the correlation assumptions from SPSS software, the results of the first and second group questionnaires are compared with SPSS software. To analyze the data and the results of the questionnaire in each step, based on the support machine, the Matlab software is used. The results of the research showed that: (1) a new method based on artificial intelligence and machine learning can be used for innovative product recycling. (2) Innovation management affects the recycling of products. (3) There is a significant relationship between innovation management indicators and product recycling plans. (4) Investigating the Support Vector Machine (SVM) in measuring the standardized researcher-made questionnaire on waste recycling and recycling behavior. |
| doi_str_mv | 10.1080/23311843.2020.1712146 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_infor</sourceid><recordid>TN_cdi_proquest_journals_2474239999</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2474239999</sourcerecordid><originalsourceid>FETCH-LOGICAL-c385t-3e2ed9d066854e87fa0c8e36b9e9cfb06553fa3889a07af951d3ed12c38fa7f13</originalsourceid><addsrcrecordid>eNp9kE1LAzEQhoMoWGp_ghDwooet-diP7E0p9QMsHqq9hmk20S3bzZpkLf33ZmkFT85lhnfedwYehC4pmVIiyC3jnFKR8ikjLEoFZTTNT9Bo0JNhcfpnPkcT7zeEkOjJU56O0GL-DU0PobYttgbvwAeNnVZ71dTtxyAZ19fB4zV4XeHoWvZdZ13AK62CdXgB6rNuNb5erhY3F-jMQOP15NjH6P1h_jZ7Sl5eH59n9y-J4iILCddMV2VF8lxkqRaFAaKE5vm61KUya5JnGTfAhSiBFGDKjFZcV5TFtIHCUD5GV4e7nbNfvfZBbmzv2vhSsrRIGS9jRVd2cClnvXfayM7VW3B7SYkc4MlfeHKAJ4_wYu7ukKtbY90WdtY1lQywb6wzDlpVe8n_P_EDdw10mQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2474239999</pqid></control><display><type>article</type><title>Evaluation of waste recycling of fruits based on Support Vector Machine (SVM)</title><source>Taylor & Francis Open Access</source><source>DOAJ Directory of Open Access Journals</source><source>EZB-FREE-00999 freely available EZB journals</source><source>ProQuest Central UK/Ireland</source><source>ProQuest Central</source><creator>Farjami, Javad ; Dehyouri, Sahar ; Mohamadi, Mohamad</creator><contributor>Akdemir, Andac</contributor><creatorcontrib>Farjami, Javad ; Dehyouri, Sahar ; Mohamadi, Mohamad ; Akdemir, Andac</creatorcontrib><description>The purpose of this research is to investigate the effect of innovation management on recycling products and to use a new method based on artificial intelligence and a machine learning for innovative product recycled management. To this end, 170 employees of fruit and berry fields were selected among the municipality of Tehran in 2015 by proportional sampling method. A researcher-made questionnaire was used to measure the attitude towards waste recycling and recycling behavior. To calculate the correlation assumptions from SPSS software, the results of the first and second group questionnaires are compared with SPSS software. To analyze the data and the results of the questionnaire in each step, based on the support machine, the Matlab software is used. The results of the research showed that: (1) a new method based on artificial intelligence and machine learning can be used for innovative product recycling. (2) Innovation management affects the recycling of products. (3) There is a significant relationship between innovation management indicators and product recycling plans. (4) Investigating the Support Vector Machine (SVM) in measuring the standardized researcher-made questionnaire on waste recycling and recycling behavior.</description><identifier>ISSN: 2331-1843</identifier><identifier>EISSN: 2331-1843</identifier><identifier>EISSN: 2765-8511</identifier><identifier>DOI: 10.1080/23311843.2020.1712146</identifier><language>eng</language><publisher>Abingdon: Cogent</publisher><subject>Artificial intelligence ; Computer programs ; fruit and vegetable fields ; Fruits ; innovation management ; Innovations ; Learning algorithms ; Machine learning ; Questionnaires ; Recycling ; Software ; support vector machine ; Support vector machines</subject><ispartof>Cogent environmental science, 2020, Vol.6 (1)</ispartof><rights>2020 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. 2020</rights><rights>2020 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. This work is licensed under the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c385t-3e2ed9d066854e87fa0c8e36b9e9cfb06553fa3889a07af951d3ed12c38fa7f13</citedby><cites>FETCH-LOGICAL-c385t-3e2ed9d066854e87fa0c8e36b9e9cfb06553fa3889a07af951d3ed12c38fa7f13</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.tandfonline.com/doi/pdf/10.1080/23311843.2020.1712146$$EPDF$$P50$$Ginformaworld$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2474239999?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,864,4022,21386,27500,27921,27922,27923,33742,43803,59141,59142,64383,64387,72239</link.rule.ids></links><search><contributor>Akdemir, Andac</contributor><creatorcontrib>Farjami, Javad</creatorcontrib><creatorcontrib>Dehyouri, Sahar</creatorcontrib><creatorcontrib>Mohamadi, Mohamad</creatorcontrib><title>Evaluation of waste recycling of fruits based on Support Vector Machine (SVM)</title><title>Cogent environmental science</title><description>The purpose of this research is to investigate the effect of innovation management on recycling products and to use a new method based on artificial intelligence and a machine learning for innovative product recycled management. To this end, 170 employees of fruit and berry fields were selected among the municipality of Tehran in 2015 by proportional sampling method. A researcher-made questionnaire was used to measure the attitude towards waste recycling and recycling behavior. To calculate the correlation assumptions from SPSS software, the results of the first and second group questionnaires are compared with SPSS software. To analyze the data and the results of the questionnaire in each step, based on the support machine, the Matlab software is used. The results of the research showed that: (1) a new method based on artificial intelligence and machine learning can be used for innovative product recycling. (2) Innovation management affects the recycling of products. (3) There is a significant relationship between innovation management indicators and product recycling plans. (4) Investigating the Support Vector Machine (SVM) in measuring the standardized researcher-made questionnaire on waste recycling and recycling behavior.</description><subject>Artificial intelligence</subject><subject>Computer programs</subject><subject>fruit and vegetable fields</subject><subject>Fruits</subject><subject>innovation management</subject><subject>Innovations</subject><subject>Learning algorithms</subject><subject>Machine learning</subject><subject>Questionnaires</subject><subject>Recycling</subject><subject>Software</subject><subject>support vector machine</subject><subject>Support vector machines</subject><issn>2331-1843</issn><issn>2331-1843</issn><issn>2765-8511</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>0YH</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kE1LAzEQhoMoWGp_ghDwooet-diP7E0p9QMsHqq9hmk20S3bzZpkLf33ZmkFT85lhnfedwYehC4pmVIiyC3jnFKR8ikjLEoFZTTNT9Bo0JNhcfpnPkcT7zeEkOjJU56O0GL-DU0PobYttgbvwAeNnVZ71dTtxyAZ19fB4zV4XeHoWvZdZ13AK62CdXgB6rNuNb5erhY3F-jMQOP15NjH6P1h_jZ7Sl5eH59n9y-J4iILCddMV2VF8lxkqRaFAaKE5vm61KUya5JnGTfAhSiBFGDKjFZcV5TFtIHCUD5GV4e7nbNfvfZBbmzv2vhSsrRIGS9jRVd2cClnvXfayM7VW3B7SYkc4MlfeHKAJ4_wYu7ukKtbY90WdtY1lQywb6wzDlpVe8n_P_EDdw10mQ</recordid><startdate>2020</startdate><enddate>2020</enddate><creator>Farjami, Javad</creator><creator>Dehyouri, Sahar</creator><creator>Mohamadi, Mohamad</creator><general>Cogent</general><general>Taylor & Francis Ltd</general><scope>0YH</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>PATMY</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope></search><sort><creationdate>2020</creationdate><title>Evaluation of waste recycling of fruits based on Support Vector Machine (SVM)</title><author>Farjami, Javad ; Dehyouri, Sahar ; Mohamadi, Mohamad</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c385t-3e2ed9d066854e87fa0c8e36b9e9cfb06553fa3889a07af951d3ed12c38fa7f13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Artificial intelligence</topic><topic>Computer programs</topic><topic>fruit and vegetable fields</topic><topic>Fruits</topic><topic>innovation management</topic><topic>Innovations</topic><topic>Learning algorithms</topic><topic>Machine learning</topic><topic>Questionnaires</topic><topic>Recycling</topic><topic>Software</topic><topic>support vector machine</topic><topic>Support vector machines</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Farjami, Javad</creatorcontrib><creatorcontrib>Dehyouri, Sahar</creatorcontrib><creatorcontrib>Mohamadi, Mohamad</creatorcontrib><collection>Taylor & Francis Open Access</collection><collection>CrossRef</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>Environmental Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environmental Science Collection</collection><jtitle>Cogent environmental science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Farjami, Javad</au><au>Dehyouri, Sahar</au><au>Mohamadi, Mohamad</au><au>Akdemir, Andac</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Evaluation of waste recycling of fruits based on Support Vector Machine (SVM)</atitle><jtitle>Cogent environmental science</jtitle><date>2020</date><risdate>2020</risdate><volume>6</volume><issue>1</issue><issn>2331-1843</issn><eissn>2331-1843</eissn><eissn>2765-8511</eissn><abstract>The purpose of this research is to investigate the effect of innovation management on recycling products and to use a new method based on artificial intelligence and a machine learning for innovative product recycled management. To this end, 170 employees of fruit and berry fields were selected among the municipality of Tehran in 2015 by proportional sampling method. A researcher-made questionnaire was used to measure the attitude towards waste recycling and recycling behavior. To calculate the correlation assumptions from SPSS software, the results of the first and second group questionnaires are compared with SPSS software. To analyze the data and the results of the questionnaire in each step, based on the support machine, the Matlab software is used. The results of the research showed that: (1) a new method based on artificial intelligence and machine learning can be used for innovative product recycling. (2) Innovation management affects the recycling of products. (3) There is a significant relationship between innovation management indicators and product recycling plans. (4) Investigating the Support Vector Machine (SVM) in measuring the standardized researcher-made questionnaire on waste recycling and recycling behavior.</abstract><cop>Abingdon</cop><pub>Cogent</pub><doi>10.1080/23311843.2020.1712146</doi><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 2331-1843 |
| ispartof | Cogent environmental science, 2020, Vol.6 (1) |
| issn | 2331-1843 2331-1843 2765-8511 |
| language | eng |
| recordid | cdi_proquest_journals_2474239999 |
| source | Taylor & Francis Open Access; DOAJ Directory of Open Access Journals; EZB-FREE-00999 freely available EZB journals; ProQuest Central UK/Ireland; ProQuest Central |
| subjects | Artificial intelligence Computer programs fruit and vegetable fields Fruits innovation management Innovations Learning algorithms Machine learning Questionnaires Recycling Software support vector machine Support vector machines |
| title | Evaluation of waste recycling of fruits based on Support Vector Machine (SVM) |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-10T02%3A09%3A39IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_infor&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Evaluation%20of%20waste%20recycling%20of%20fruits%20based%20on%20Support%20Vector%20Machine%20(SVM)&rft.jtitle=Cogent%20environmental%20science&rft.au=Farjami,%20Javad&rft.date=2020&rft.volume=6&rft.issue=1&rft.issn=2331-1843&rft.eissn=2331-1843&rft_id=info:doi/10.1080/23311843.2020.1712146&rft_dat=%3Cproquest_infor%3E2474239999%3C/proquest_infor%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2474239999&rft_id=info:pmid/&rfr_iscdi=true |